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Energy-Efficient Computation Offloading in Collaborative Edge Computing

delete2022-11-01
delete20
PRE
AI
R
Rongping Lin *
T
Tianze Xie
S
Shan Luo
X
Xiaoning Zhang
肖
肖泳 (Yong Xiao)
B
Bill Moran
M
Moshe Zukerman
DOI:10.1109/JIOT.2022.3179000delete
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摘要

摘要

En 中文
Edge computing is an indispensable technology that overcomes delay limitations of cloud computing. In edge computing, computational resources are deployed at the network edge, and computational tasks and data of end terminals can be efficiently processed by edge nodes. Considering the computational resource limitations of edge nodes, collaborative edge computing integrates computational resources of edge nodes and provides more efficient computing services for end terminals. This article considers a computation offloading problem in collaborative edge computing networks, where computation offloading and resource allocation are optimized by means of a collaborative load shedding approach: a terminal can offload a computing task to an edge node, which either can process the task with its computing resource or further offload the task to other edge nodes. Long-term objectives and long-term constraints are considered, and Lyapunov optimization is applied to convert the original nonconvex computation offloading problem into a second problem that approximate the original problem and it is still nonconvex but has a special structure, which gives rise to a new distributed algorithm that optimally solves the second problem. Finally, the performance and provable bound of the distributed algorithm is theoretically analyzed. Numerical results demonstrate that the distributed algorithm can achieve a guaranteed long-term performance, and also demonstrate the improvement in performance achieved over the case of computation offloading without collaborating edge nodes.
Keyword:
Task analysis
Collaboration
Edge computing
Resource management
Cloud computing
Energy consumption
Delays
Collaborative edge computing
computation offloading
Lyapunov optimization

期刊

IEEE Internet of Things Journal 封面图
IEEE Internet of Things Journal
IF:
8.9
论文数:
1.4W
被引数:
8.3W

机构

C
City University of Hong Kong
学者数:
2.6K
论文数: 1.2K
被引数: 0
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